Role of Test Automation in DevOps

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DevOps is a multidisciplinary approach that creates an advanced development environment by combining development, IT operations, modern practices, and tools. When test automation is carried out along the DevOps pipeline it aids in faster deployment of the software. DevOps supports continuous integration and continuous deployment (CI/CD), allowing the testing to be conducted earlier in the software development cycle. When testing is conducted earlier, it offers a much larger scope to improve the product quality by rectifying the errors/bugs in the earlier stage, which would otherwise amplify and cause severe issues if left unidentified earlier.

The success of the DevOps lifecycle depends on test automation which ensures that the developed software quality is top-notch. Continuous testing is a critical part of the DevOps cycle that lowers the operational and infrastructural risk and facilitates greater quality and improved speed, reduced cost, and increased accuracy. Hence, the success/failure of the end-product depends on developing it in a DevOps environment and implementing automation testing along the pipeline.

 Test Automation and DevOps

DevOps is the modern-day software development approach that can achieve the desired speed and agility by implementing test automation. Automation testing plays a pivotal role as it supports the dynamic CI/CD pipeline of the DevOps cycle. DevOps is a cultural shift that organizations are embracing for better and faster deployment, and test automation improves the quality with nearly 100% accuracy.

By implementing test automation, DevOps practice can benefit from the following:

  • Increases the process reliability
  • Test automation can detect the bugs earlier, hence, making the product deployment easier and quicker
  • The error rate is considerably reduced
  • Simplifies the process and promotes accurate and faster test case execution

Fig – DevOps Lifecycle

In the DevOps cycle, the test automation process has taken a shift-left approach, wherein testing is performed from the beginning of the software development cycle, reducing the length of delivery time while improving the quality of the release. This approach is purely focused on improving the quality to offer a great user experience, which will eventually improve the brand value and ROI.

How does the Automation Testing Process improve the previous cases?

The automation Testing process reduces the SDLC life cycles and follows the points mentioned below to improve the previous cases –

  • Improves speed
  • Offers fast feedback
  • Provide reliable results
  • Efficient result
  • Minimizes time and cost
  • Minimal human intervention

What role does Automation Testing play in DevOps?

Test Automation plays a crucial role in the following situations:

  • Incorporating test automation in DevOps, manual testing is minimized considerably as the automation processes take over. As the process is automated, the obvious human errors can be reduced and proven to be successful for repeated executions and regression tests.
  • It comparatively becomes easier to check an application after each step than to compare it at the end of the deployment. It makes it easier to correct each step than finding bugs after completing the software.
  • As advanced coding knowledge may be required for conducting testing at the API level, automation testing handles this task with ease as the process is automated and does not demand any coding knowledge. However, coding may be required only to set the process.
  • To correct the test cases in an estimated time limit and remove the errors, developers must change the code multiple times. The automation testing process offers an easy way to overcome these problems.

How to make test automation successful in DevOps

Here are a few points to consider yielding the best results from using test automation in DevOps:

Implementing testing simultaneous to the development

In the DevOps cycle operating on a continuous release approach, testing is carried out simultaneously to the development. By following this approach, issues can be fixed early and efficiently. This is an efficient way to reduce cost and improve time-to-market with improved quality.

Flexible test scripts

As the DevOps process consists of continuous integration, it is important to create flexible test scripts of higher quality to support the continuous integration process. The flexible scripts will support regression tests to ensure high accuracy and performance.

Choosing the right automation tool

It is important to choose the right test automation tool that will support the DevOps process efficiently. Make sure to use the tool that possesses all the capabilities that will suit your requirements.

Maintaining single test flow

It is recommended to test one thing at a time. Single flow testing will reduce the process complexity and makes it easier to find out the faults. Running multiple tests at a time can be a cumbersome process.

Building reusable test cases

Building reusable test cases will considerably reduce the time, cost, and hassle being taken to create a new test case. Organizations have reported that they have saved immense time and cost by creating reusable test cases.

Codeless test automation

Codeless test automation is the ideal choice for testing in a DevOps environment as it allows easy and faster product release across the complex CI/CD pipeline. Codeless test automation helps achieve the business objective by improving quality while reducing cost and risk.

Yethi’s test automation solution for banks and financial institutions

DevOps is the trend in the software development process banking and financial software processes are no different. To support the complex banking/finance software and ensure the developed software system is of high quality, Yethi offers a world-class test automation solution. Its test automation platform, Tenjin, is a 5th generation tool with robotic UI plug and play capabilities that can automatically learn and relearn to give higher testing accuracy.

Tenjin will help address the functional and non-functional issues in the complex banking/financial software system. With its half a million-test case repository, Tenjin can significantly help reduce time, effort, and money.

Data Migration Testing: Strategy & Best Practices

data migration blog cover image

As the world is witnessing a huge transformation at the technological front, organizations are constantly upgrading their legacy systems to keep up with the trend. Though updating to new systems is the need of time, a major challenge lies in migrating data without losing it. Hence, it becomes important to plan out an efficient data migration strategy to ensure that migration happens without any data loss.

Testing of migration is as important as migrating data; failing to do so, organizations may face issues of discrepancies causing expected results, which can affect the organization adversely. Furthermore, to carry out efficient migration testing a well-defined strategy is required, without which the organization can be left financially drained of resources after setting up more processes than they need. They may even find that their commercial success is negatively influenced by not exploiting their data to the fullest.

What is Data Migration? Why Do Organizations Undertake Data Migration?

The process of moving data from one system to another, preferably from a legacy system to a new one, is known as data migration. However, the process is not as straightforward as it may seem because it involves a change in storage and database or application. The data migration process involves three defined steps extracting data, transforming data, and loading data. When the data is extracted from the sources, it must go through a series of cleansing to eliminate errors and inaccuracies to qualify the data for efficient analysis and load them to the targeted destinations.

Organizations perform data migration for varied reasons; first, as a part of their system revamping plan, the other possible reason could be during the upgrade in databases, while another possibility could be when creating a new data warehouse or merging data from acquisitions. But it’s most common when teams are deploying other systems alongside their existing applications for integration purposes.

Why is Data Migration Strategy Important?

A comprehensive data migration strategy comes in handy when performing large-scale operations that need to preserve business continuity simultaneously. Organizations perform data migration to improve performance and competitiveness. When organizations carefully control the data migration process, they can prevent delays caused by missing deadlines or exceeding budgets, while improperly managing the process can leave a lot of migration projects dead in their tracks. In planning and strategizing the work, teams must ensure that they put their best foot forward with undivided focus on one project.

Data Migration Strategies

There are several approaches to developing a data migration plan, however, the two major data migration strategies include “big bang” or “trickle.”

  • ·         ‘Big Bang’ Data Migration

Organizations follow big bang data migration to ensure that the data is moved from the legacy systems to the target destination and the full transfer is done in a limited time. As the data migration process goes through the three inevitable steps of extraction, transformation and loading, the active system may experience a little downtime towards transitioning to the new database. The data migration process has some challenges like validation implementation failure, lack of data analysis scope, and inability to validate specification to name a few. But companies implement this strategy as the entire process of data migration takes less time to complete even with many challenges

  • ·         ‘Tickle’ Migration

Tickle migration is conducted in phases to avoid downtime or operational interruptions. In addition, migration staging is conducted continuously to support migration, even during peak operations.

Key Components in Data Migration Strategies

Moving sensitive or important data isn’t a simple task as it involves a lot of aspects that would need consideration. Hence, it is not a good idea to begin the process without having a plan on how this should be done. One must consider the key components of data migration strategies based on the critical factors mentioned below.

  • Knowledge of data — It is critical to have adequate knowledge of the source data to find the solution to issues that may arise unexpectedly. Hence, consider doing a thorough audit of the source data before migration.
  • Data cleansing — Between source data extraction to data transformation, there is a critical step of data cleaning, which focuses on identifying the issues of source data and resolving them.  The data cleaning can be done using software tools and third-party resources. 
  • Data quality maintenance and protection — The quality of data may subside over a period. It is critical to maintain and protect the data quality to ensure the reliability of the data migration process.   
  • Data tracking and reporting — It is critical to ensure data integrity by data tracking and reporting. Use the right tool and automate the function wherever needed.  

Although we can follow many ways to move data, it is important to have adequate knowledge about the best practices to ensure that the process of data transfer is done systematically and seamlessly.

  • ·         Solid Planning

Good planning is half work done. Decide the systems that will need to be migrated and plan how they will affect the business. When migrating data from one system to another, always ask yourself if your changes can be made without affecting or hindering other systems already being used by the business. Solid planning will help in carrying out the entire process with utmost ease.

  • ·         Action Steps

It’s time to give your migration process a ticking clock and a detailed, step-by-step plan– including the plan of execution – what, who, why, and deadlines – to ensure your migration is successful and time-bound.

  • ·         Crosscheck

Decide what technology to use for the migration and how it will fit into the larger IT ecosystem. Make sure you have a plan in place for decommissioning old systems.

  • ·         High-Quality Conversion Process

Ensure you map out the technical details related to how you plan to move data. Then, put processes in place to ensure that your data stays organized and of high quality.

  • ·         Build & Test

Here, you will implement the software logic that performs the conversion of data. Test the script in a mirror sandbox environment instead of running it against your production database.

  • ·         Execute

You’ll need to verify that data migration processes are safe, reliable, and fit for use in your business before implementing them.

How to Make Your Data Migration Go Smoothly?

Transferring sensitive data is a complex yet delicate process. However, here are some best practices to follow to ensure a successful migration.

  • ·         A Thorough Migration Plan

It would help if you had a good idea about how much data to move, from where it will come, and an idea of how you’re going to implement its move into your target server or location. Your plan should outline each necessary step and who will be responsible for them, physical aspects such as technical or compatibility issues, downtime expected for your system, and the source data and migration tools if they are going to be used. Last but not least is protecting your data’s integrity. Backups may prove exceptionally helpful in preserving your original data.

  • ·         Examine your Data

Before you proceed, take a close look at the data that you’re going to be migrating. In particular, identify and weed out data that is outdated and no longer important. Separating it from your migration will help streamline your process and set a clean slate for your team after the migration is complete. If there are pieces of information that require security controls due to the nature of its regulatory information, make sure you take these details into account.

  • ·         Put Migration Policies in Place

A data migration policy ensures that your data is on the right path after it’s been migrated. It also organizes and gives control over who will handle it and how they will do it, along with adequately protecting your company’s sensitive data.

  • ·         Automatic Retention Policy

Once you’ve successfully migrated, you must take the time to ensure that everything is placed where it belongs and remains safe and secured. It’s essential to keep all your systems in working order by setting up automatic retention policies to prevent data leakage. Also, make sure that outdated data has been validated and permissions are granted accordingly. Finally, just ensure that old legacy systems will back up automatically in the event of any technical difficulties – but make sure to double-check them before they’re put on standby!


As technology continues to change, businesses must continue to evolve as well. As a result, companies must create a plan for their data and understand data migration in today’s business world. Data migration can be challenging, but a company can migrate its data with minimal downtime and stress with a proper strategy and a few best practices.

At Yethi, we have the expertise of handling complex financial data migration, with pre and post-migration testing along with regular audits. We offer the most efficient end-to-end testing service. Our test automation platform, Tenjin, can test large data migration easily and efficiently while reducing time and cost significantly.

Challenges associated with transformation projects from Legacy System to Digital Platforms

Transformation from legacy systems to the digital platform

One of the major challenges that lie ahead of digital transformation is the legacy systems that the businesses run on.  Legacy systems are the software programs that have remained in use with the organization since its establishment or for several years.

With the modern technological advancements, the legacy system fails to keep up with the pace and often becomes outdated and unfit for business uses. It can hinder the efficiency of the operation process if data sets and other information can be leveraged to the extent of modern systems.

Hence, it becomes necessary either to upgrade or replace the legacy system to keep up with the current trend. Failing to do so, the organizations may not survive in the highly competitive market and may lose their business value. Hence, regular update/ upgrade or replacing the legacy system is required to align with modern-day digitization and improve the ROI metric of the organization.

Though the upgrade of legacy systems is inevitable, it is often a daunting experience to update them. Organizations should address the associated challenges with the legacy systems and resolve them for a smooth transformation to digital platforms. Once they are upgraded, they will ensure to offer an efficient operational and infrastructural process being leveraged by modern technology.

Legacy Systems: Everything you should know

Do you remember your first smartphone? How would you rate it in comparison to the one you have today? Undoubtedly, the one that you own today is way more advanced in terms of features and functionalities compared to the one that you had a decade ago.

Likewise, companies install a certain system at the time of their establishment which, over time, gets outdated and underperform. It is important to upgrade the system periodically to yield the best business outcome, but there can be a few challenges to upgrading the legacy systems. One such challenge is that it can be cumbersome, unruly, and challenging to update. End users might also be complacent with their existing systems and may be reluctant to transform their legacy platform.

The Characteristics of Legacy Systems explained

  • The system still fulfils the purpose it was initially meant for
  • They are not well integrated with other modern business solutions in use
  • The old technology of these systems does not allow it to interact with newer, modern systems
  • They do not permit the growth of the business tools and solutions specific to a company
  • Their support and maintenance services are longer available from the service provider
  • They are incompatible with modern and advanced solutions
  • It requires frequent patch upgradation
  • It requires multiple interfaces or multiple standalone systems / in-house systems to run the business smoothly and efficiently
  • It requires heavy customizations
  • It runs on obsolete technology  

Due to these limitations of legacy systems, organizations are adopting modern technologies that can provide solutions with greater efficiency, scalability, and adaptability.

Risks & Issues with the Existing Legacy System

  • Maintenance

Legacy systems typically have a huge codebase and are monolithic in nature. A little modification or replacement of one system module or even a small update can create conflicts across the system. It requires more time and effort to implement any new changes.

Every system in an organization requires regular maintenance to calibrate the system, clean up the junk data of the existing database, and ensure its efficiency is not compromised. Outdated software is hard to maintain in recent times as it is difficult to find the people with the required expertise and skillset. The maintenance cost of legacy systems can also be expensive.

Further, these systems have been loaded with large amounts of corporate data for years, the struggle of migrating this data-intensive system to a new platform can be full of hassles. An inefficient maintenance process may give rise to unexpected defects, which further leads to operating issues. Workforces familiar with handling modern IT solutions might face issues in managing old systems that reduce the operational speed.

  • Talent pool

Developers who are just starting are learning programming languages like JavaScript and C#. As legacy technology moves further past the point of manufacturer support, there are fewer and fewer IT professionals with the knowledge of those technologies. Thus, the costs of the smaller pool of experts in that technology grow. 

  • Cyber Security:

Cyberattacks are rising, which increases the cost of running legacy systems. Systems with obsolete infrastructure are highly vulnerable to cyberattacks due to inadequate protection and cyber protocols. The bottlenecks in these legacy system solutions pave the way to cyber-attacks and malicious tasks.

Organizations cannot afford to remain non-compliant with the latest security standards. It does not safeguard their systems from potential threats. A single unpatched vulnerability can enable attackers to access all applications, middleware, and databases running on the server platform.

Thus, associations still holding on to legacy systems are prone to risks of unauthorized access and neglect of their safety. This burdens developers with the priority to protect their systems and prevent hackers from fetching essential information.

The number of attacks that lead to privacy breaches is escalating every year. It can cost millions of dollars penalty to an organization. Hence, the Cloud storage system is becoming a booming substitution for legacy systems with enhanced security features.

  • Integration:

The most significant disadvantage of any legacy system is its inefficiency in integrating modern advanced software. A typical result of this lack of integration is the emergence of data silos, whereby different departments across a company cannot freely access the data they need.

Many modern clouds and other SaaS solutions can be incompatible with older legacy systems. It requires incorporating new tools and programs, extensive custom code to make it functional. The incompatibility of these applications gives rise to tedious steps that need to be followed in data migration.

Companies looking for development in their work processes face tremendous hassle in opting for suitable techniques that will build a bridge between legacy systems and present-day IT solutions. One of the most preferred technologies of this era is the Cloud storage service that covers up most of the loopholes present in the old systems.

  • Organizational agility and efficiency

Timing is extremely crucial to seize business opportunities. How fast can you respond to the market challenges? Will it take weeks to adopt new technologies and solutions? Or rather several months? The truth is, in most cases, businesses bound to legacy systems lack organizational agility to adapt to the upcoming challenges.

One of the most damning implications of continuing to use a legacy system is the stifled ability to modernize and improve. The most significant goal in digital transformation strategy is improving efficiencies and capabilities to remain competitive. Legacy systems in business are extremely inflexible, which becomes an obstacle for most organizations operating in today’s digital environment.

Customers expect organizations to be digitized, and executives see the digital transformation to be competitive. By not investing in new technology and sticking with a legacy system, you’re hampering your ability to compete and giving ground to your competitors. Maintaining data on Cloud is cost-effective compared to maintaining on Premises. It is more convenient to get access to the data when it is on the cloud than fetching it from on Premises.

  • Performance & Productivity:  

Legacy systems become slower and slower over time, which means performance, efficiency and productivity can also decrease. The older your application gets, the slower it becomes. Legacy systems usually consume more resources causing more frequent failures, which leads to inefficiency and unproductivity. As performance speed depends on the optimal usage of technology capabilities

The technology sector is fast-paced, and evolutions in software are emerging every day. A poorly performing software has no chance to stand out in the market, eventually incurring a huge loss to the company. Legacy Systems lack performance, efficiency, and productivity as they are incompetent with the modern approach. Therefore, upgraded systems can undoubtedly provide better data accuracy and speedy processing.

7 reasons why digital transformation of Legacy Systems is necessary for Business

Some of the advantages of transforming your systems digitally are as follows,

  1. Competitive advantage: Modernizing a legacy system, whether it’s an ERP, CRM, or your data center, can bring a plethora of advantages to your business. This allows you to become more capable, agile, and give you an upper hand over your competitors.
  2. Maintenance and Operation Cost: With the support of In-house staff like engineers and developers, organizations will be able to maintain and reduce operational costs. Organizations can also use third-party tools to fill the missing features of the systems. It would be easy to streamline the task whether automated or manually for the employees.
  3. More content employees: User interfaces have evolved significantly over time, and most employees will be accustomed to the modern UIs that improve customer satisfaction and performance over an older-style system that’s not as user-friendly. 
  4. Growth opportunities: Modernizing your legacy system gives you much more room for growth in the future.  Keeping pace with the latest tech and software developments gives you a competitive edge. It also puts you in a great position to further expand the services you use.
  5. Make use of big data: A major issue posed by legacy systems that digital transformation attempts to remediate is the silos that emerge from disparate systems within an organization. Transforming the legacy systems digitally remove these barriers and allow users to make use of the vast amounts of data big data that the Bank possesses to help support business decisions.
  6. Security and Performance: Digital transformation is highly secured compared to the legacy system. From the performance point of view, digitalization will be able to meet the expectation of the NextGen group and tap the market with new additional business from the Next G population as well as cope with the fast-moving pace of the global market.

How can a thorough test automation solution help in moving from legacy systems to digital platforms

When an organization is planning to upgrade its legacy system or move to new digital platforms, it is essential to conduct thorough test automation to ensure the new system is working seamlessly.

Successful automation strategies leverage the convergence of digital technologies with evolving systems to enhance the benefits gained by any organization. Digital technologies involving codeless test automation, automated regression testing, artificial intelligence, machine learning, and natural language processing have boosted productivity and accelerated the end-to-end process transformation. As a result, the steps to centralize, standardize, optimize, and automate software processes have become a lot more straightforward.

To ensure that the data is efficiently moved from the legacy system to the modern platform, it should be made sure that it is moved with minimal disruption and minimum data loss, in the most secure and scalable manner. Further, it should be made sure all the functional and non-functional objectives are achieved. Testing helps to achieve all the above said with increased speed, accuracy, consistency, and ROI.

How can Yethi help you?

Yethi is a niche QA service provider to banks and financial institutions worldwide. We assist professionals from the BFSI industry looking for end-to-end software testing solutions like Manual Testing, Automation Testing, Performance Testing, Security Testing, and more to improve Banking / Financial software quality.

We understand the importance of testing while moving from legacy systems to modern platforms, hence, we carry out thorough test automation to ensure the high quality of the system. We have the right resources and tools to carry out testing in the most efficient manner and yield the expected outcome. Our test automation platform, Tenjin, will perform all kinds of testing activity with utmost accuracy, precision, and consistency with nearly 100% results. It is a 5th generation codeless test automation tool; Tenjin is built with intuitive features that work flawlessly across multiple applications and is a fast and scalable test automation platform.

Data Integration Architecture and Customer Experience – A performance viewpoint

Cover image for the data integration architecture by Yethi

Data is omnipresent. It is available across multiple applications, data warehouses, databases, and even the public Cloud in every organization. Data belongs to various groups within an organization and is commonly shared across teams and applications.

As an organized sports team has a clear division of responsibilities, each with a dedicated role to play and win; organizations should ensure all departments have specific roles and coordinated effort from functional units to get the most out of their resources and get things done right. To make sure everything is cooperating effectively, companies need to work towards improving their data integration architecture. This will help them keep track of what is going on and share information in real-time, which gives them better insight into how things are progressing and where there might be opportunities for improvement.

What is Data Integration Architecture?

Data integration architecture is the engine driving the business data ecosystem, where people can focus on generating customer value. Too often, users spend time searching for data rather than using it to create new products or find ways to increase sales. A Data Integration Platform supports critical functions of an enterprise by allowing users to consolidate data from multiple sources into a single platform, transforming information into actionable knowledge, and seamlessly sharing that data across the organization for business decision making.

Why is Data Integration Architecture Important?

It’s important to create a data integration architecture to help you integrate whole data and normalize it to support faster decision support and innovation. Your company depends on the analytics and insights gleaned from all sorts of data. Having a dependable data integration architecture in place is so important when supporting these business functions.

Creating a data integration architecture does not mean creating a framework that combines all of your enterprise’s information source into one system, like a giant database or big data analytics

There are more issues like storing, managing and analyzing complex and large data in banks and financial institutions. Through data analytics, organizations can solve these issues. Financial organizations have realized the importance of data analysis and are slowly adopting these changes to improve accuracy and efficiency. 

Typically, there are multiple databases in financial industries that store the data. The banking data is complex and spread across many systems. It is challenging to unify the data into a single data warehouse from multiple systems. Banking professionals use data integration architecture or data warehouses to simplify and standardize the way they collate the data and create a single database.

Instead, it means understanding how different systems and tools across your organization communicate to share accurate and relevant information across the company. Data integration architecture helps define how relevant information can be shared between internal departments and external business partners through compatible technologies – usually ensuring that companies avoid ineffective redundancies and achieve better functionality and streamlined teamwork across the board.

Factors to be Considered

As analysts pursuing business intelligence, you must know how challenging it can be to find the method of data integration that will most ensure access and availability and flexibility for analysis.

Consider the following:

  • How many different data sources do you need to integrate?
  • Your data set’s size and format.
  • Your source data’s reliability.

Data integration should be considered by companies to embark on achieving their goals, which may take a combination of different methods and tools to accomplish.

Types of Data Integration

As analysts, make sure to consider multiple types of data integration methods for your business. It’s crucial to find the method that best suits the insights you need as a business, as well as what you’ll be using your data for.

Data Consolidation

Data consolidation is a method of acquiring data from different sources and usually requires specialized software with a query interface to combine data from multiple sources into a single database.

Data Propagation

Data propagation is a method of integration that duplicates data stored in source data warehouses. This can be used to transfer data to local access databases based on propagation rules.

Data Federation

Federating data means connecting various pieces of information so they can be viewed centrally. Data federation is a technology that allows companies to link together data from multiple sources using a kind of ‘bridge.’

Data Integration Techniques

There are several data integration approaches to choose from, each with its own set of capabilities, functions, benefits, and limitations.

  1. Manual Data Integration: The process of locating information, accessing different interfaces directly, comparing, cross-referencing, and combining it yourself to get the insight you need is a manual data integration.
  2. Application-based integration: Application-based integration is the process of accommodating individual applications, each with their unique purpose, to work in conjunction.
  3. Middleware Data Integration: It serves as a “layer” between two dissimilar systems, allowing them to communicate. For example – The architecture in Finacle 10x is SOA, which has middleware that integrates with CRM to offer a 360-degree view of customers and learn about the customer experience.
  4. Uniform access integration: Uniform access integration is a type of integration that focuses on developing a uniform translation process that presents information obtained from multiple sources in the best way possible. It does this without having to move any information – data remains in its original location.

How Data Integration improves performance and customer experience

Understanding your customer, their needs, and their purchasing preferences are essential parts of any successful business. With the amount of data about your customer available to you right at your fingertips, it’s becoming easier for any entrepreneur to build a successful customer-driven strategy. However, with most data now being stored digitally, the challenge today is to quickly assess and apply all this large amount of data with limited resources!

There is a lot of data that’s floating around for you to take into account. With so many numbers and figures to consider, it can sometimes become difficult to determine which information is helpful and which isn’t. Luckily, having a customer data integration tool can help you better understand your consumer base by providing valuable insight and ways to reach those consumers as well as manage those.


Data integration architecture is the process of combining data from different sources into a single system. This data is then structured to be used for a specific purpose, such as a marketing campaign or a manufacturing process. Data integration architecture uses tools and technology to combine data from multiple sources. This process can have several benefits, including improved performance and a better customer experience.

Risk-based Testing: Uncovering Risks

Risk detection

Risk-based testing starts early in the project by identifying the risks to the quality of the system.  This knowledge is used to guide the planning, preparation, and execution of testing.  The testing begins early in the project by identifying the risks to ensure the quality of the system.  Risk-based testing included mitigation testing which would offer opportunities to reduce the possibility of defects.

In risk-based testing, the quality risks are identified and assessed with stakeholders through a product quality risk analysis. The testing team designs, implements, and tests to reduce the quality risks.

Each product could convey a different grade of risk after identifying the parameters impacting the same and grading them.  Depending on the grades worked out, the classification as high, medium, and low risk is done. The intensity of the approach depends on the level of risk.

Need for risk-based testing:

Risk-based testing helps in reducing the remaining level of product risk during system implementation. The testing is done in the beginning stages of the project and helps all the persons involved to control the SDLC/STLC.

Risk for each product is investigated from processes and procedures, which are then graded. This method of quantifying risk allows testers to determine each risk’s overall impact and predict the damage caused by failure to test specific functionality. The strategy includes risk severity-based classification tests to identify the worst or most risky areas affecting the business.  It uses risk analysis to predict the likelihood of avoiding or eliminating defects using non-testing procedures and to help the organization select the necessary testing actions to perform.

The benefit of risk-based testing is to cut short timelines with optimal coverage.  It helps banks or financial institutions to lay their focus on high-risk areas in terms of q/a.

The above will help in reducing the efforts and costs without compromising on quality.

Yethi has out of its own experience, developed strategies and scoring patterns to help identify the risk level and the consequent impact on the project execution.

Action plan

Identify the risk

Risks are found through different testing methods and categorized accordingly. A chart is prepared based on the risk weightage and impact on the product.  The process involves organizing different risk workshops, checklists, root cause analysis, and interactions.

Risk analysis

Based on the risk parameters, ranks are allotted based on the probability and consequences that may follow.

A register or a table is used as a spreadsheet with a list of identified risks, potential responses, and root causes. Different risk analysis strategies can be used to manage positive and negative risks.

Response strategy

Based on the risk, the team chooses the right test to create a plan of action. Document the dependencies and assign responsibilities across the teams. In some cases, the risk strategy is conditional on the project.

Test Scoping

A review activity that ensures that all stakeholders have hearsay along with the tech staff.  Risk scoping helps create backup plans based on the worst-case scenarios, just to be prepared for a cascade of failures.

Identify the probability and high exposure areas and analyze the requirements.


After all parameters and scope of testing are listed out, testing needs to be carried out in stages. Prepare a risk register to record all developments from the initial risk analysis, existing checklist, and brainstorming sessions.

Perform dry test runs to ensure quality is maintained at each stage.

Maintain traceability between risk items and at every level of testing, e.g., component, system, integration, and acceptance.


Risk-based testing systems are sophisticated, efficient, and entirely project-oriented that resulting in minimizing risks. The testing efforts are quite organized, where each test has a protocol based on risk probability.

Testing Strategy for Big Data Migration

cloud architecture

Big data migration is way more complicated than a mere “lift-and-shift” migration. One of the major concerns is data security when migrated to the cloud. Companies adopt hybrid cloud solutions to protect sensitive data. They differentiate computing and storage data and implement role-based access to ensure data safety on the cloud.

As big data has already created a lot of buzzes recently, organizations across all major sectors are trying to leverage it for their organizational growth. But due to a lack of technical skills and knowledge of data integration practices and tools, developers cannot always fully ripe the benefits of a cloud-based big data environment while moving the on-premises data to the cloud.

Big data is a field that deals with the identification and evaluation of voluminous and complex data sets, and migrating these voluminous data requires monitoring, which increases operational costs. The code-writing process is usually time-consuming, and without automation, it has a high risk of human error. It is important to note that big data does not focus on quantity. Instead, it focuses on extracting meaningful information from these data, which the company can utilize.

When organizations upgrade their legacy systems, they undertake the most complex task of big data migration. The migration process requires a clear testing strategy and an efficient team to prevent data loss.

What is Big Data testing?

Big Data testing is a set of methodologies that ensure whether different Big Data functionalities and operations perform as expected. Enterprises perform Big Data testing to assure that the Big Data system runs smoothly, without any error/bug. The test also checks the performance and security of the system. Big Data professionals perform such testing when they have updated the software, integrated new hardware, or after data migration. Big Data migration testing is the essential phase of data migration as it checks whether all the data got migrated without loss or damage.

Big Data is an accumulation of data with a large volume of greater variety, that grows exponentially with time. Every enterprise generates a vast collection of data which is so voluminous that it becomes difficult for the conventional data processing applications to handle them. Hence, Big Data technologies, software, and methodologies are created to deal with challenges associated with big data processing. Big Data deals with the three V’s – Volume, Velocity, and Variety, which has eventually become the mainstream definition of Big Data.

Data Migration and its Challenges:

The technological evolution has led every enterprise to migrate its data to advanced systems. The prime reason for migration is the availability of the Cloud. Migrating this immense volume of data to the Cloud helps productivity improvement, cost reduction, and flexibility in data management for the organization. When such a large volume of data migrates to the Cloud, Big Data migration testing becomes a vital phase. It checks the condition and connectivity of the overall data. Data migration has to face a wide array of challenges. Some of them are:

  • Mismatched data type:

During data migration, the data type needs proper mapping. It is essential to check the variable-length fields.

  • Corrupt data or incorrect translation:

For a single Big Data storage, multiple source tables store various formats of data. It is crucial to conduct a thorough data analysis when the architecture shifts from a legacy system to a modern Cloud-based system. The verification will check whether any data is corrupt or not.

  • Data loss or data misplace:

Data migration also experiences another critical issue, which is data loss. It happens when data backup takes place or there exists some illogical analysis of data.

  • Rejected row:

When data shifts from the legacy system to the target system, some data gets discarded during data extraction. It usually happens when automatic migration of data occurs.

Strategies in Big Data Migration Testing

Big Data migration testing is an essential phase of migrating large data volumes. Various types of testing occur before and after the migration. The big data testing team has to prepare some strategies to cater to the multiple testing to understand the data validation and outcome of the test. The phases of big data testing strategy include:

  • Pre-migration Testing: There are several testing strategies and techniques that take place before the data migration.
    • The team should understand the scope of the data correctly. It includes the number of tables, record count, extraction process, etc.
    • The testing team should also have a fair idea of the data scheme for both the source and the target system.
    • The team should also validate whether they can understand the data load process or not.
    • Once the test team understands all these, they should now ensure whether the mapping of the user interface is correct or not.
    • The testing strategy should also involve ensuring & understanding all business cases and use cases.
  • Post-migration Testing:

Once the data gets migrated, the tester(s) should accomplish further tests against the subset of data.

  • Data validation and Testing: This test ensures whether the data collected to the new target system is correct and accurate. The team performs this validation by entering the collected data into the Hadoop Distributed File System (HDFS). Here a step-by-step verification takes place through different analytic tools. The schema validation should also come under this phase.
    • Process Validation: Process validation or Business logic validation is where the tester checks for nodes associated with the business logic at every node point. This process uses Map Reduce as the tool, which validates the key-value pair generation.
    • Output Validation: The last phase of the big data migration testing is where the data gets loaded into the target system. Then the Big data testing team should check whether the data has experienced any distortions. If there is no distortion in data, the testing team transfers the output files to the Enterprise Data Warehouse (EDW).

Big Data Migration Testing Tools

A variety of automation testing tools are available in the market for testing Big Data migration. The test team can integrate these tools to ensure accurate and consistent results. These tools must hold certain features like scalability, reliability, flexibility at constant change, and economical.


Due to the exponential increase in data production, organizations are shifting their data storage technique to Cloud. Hence, Cloud has become the new standard, and Big Data migration has become necessary. So, while shifting from legacy data storage techniques to the latest technological advancement, every organization should perform big data migration testing to check the data quality.

Yethi is a leading QA service provider for global banks and financial institutions. We understand the importance of complex financial data migration and make sure to offer the most efficient testing service. We have the expertise to handle complex data migration, with pre and post-migration testing along with regular audits. Our test automation platform, Tenjin, can test large data migration easily and efficiently while reducing time and money significantly.

What is Static Testing


Organizations do not immediately execute software testing after receiving the project details. From acquiring project details to test execution there is a critical step of requirement validation that deals with related documentation and helps in smoothening the testing process. It is an essential step in the software development and testing processes, which cannot be neglected. While testing helps understand the efficiency of the code and other functionalities and identifies any errors or discrepancies that affect the quality of the software, requirement validation and documentation help you prepare for software test execution. The checking of this documentation comes under the purview of static testing.

There are two critical methods of Testing; they are Static Testing and Dynamic Testing.

Static Testing: It is a testing method that allows a user to examine the software/program and all the related documents without executing the code.

Dynamic Testing: On the other hand, dynamic testing checks the application when the code is executed.

Both these methods are essential and frequently used together to ensure that the applications are functional. However, this article highlights the static testing approach, which is crucial for the software development lifecycle but often is taken for granted. It is an assessment process to check the code and requirement documents to find errors early in the development phase.

Why is Static Testing used?

Static testing is performed to check the code and design documents and requirements for coding errors. The aim is to find the flaws in the early stage of development. Static Testing makes it easy to find sources of potential errors.

The users and developers static test the code, design documents, and requirements before executing the code. Checking the functional requirements is also possible. The process explicitly reviews the written material that gives a broader view of the software being tested.

Following are some documents that are checked during the Static Software Testing Process.

  1. Requirement Specifications
  2. Design documents
  3. User documents
  4. Web page content
  5. Source code, Test cases, test data, and test scripts
  6. User documents
  7. Specification and matrix documents

What are the errors that can be detected during Static Software Testing?

 Types of defects that can be easier to find during static testing are as follows –

  1. Deviations from standards
  2. Non-maintainable code
  3. Design defects
  4. Missing requirements
  5. Inconsistent interface specifications

Why is Static Testing used?

Static Testing is specifically used to identify any flaws in functionalities or possible coding errors in the initial stages before the code is executed.

Following are some benefits of using Static Testing –

  1. Detection and correction of potential coding errors
  2. Cost Efficiency – A reduced cost that goes into rework to fix errors
  3. Time Efficiency – A reduced time that goes into rework
  4. Feedback received at this stage helps improve the functioning of the project
  5. Once the developer moves to Dynamic Testing, the number of errors is limited. It makes the code maintainable
  6. The process also helps the developers identify the quality issues in the software
  7. There are automated tools available that make this process of reviewing the code and other documents faster and easier
  8. Static Testing also boots communication among inter-functional teams

What are Static Testing Techniques?

Static Testing is carried out in two steps –

  1. Static Review
  2. Static Analysis

Static review is done to find and rectify ambiguities and errors in supporting documents like requirement specification, software design documents, and test cases.

These documents can be reviewed in various ways, such as –

  1. Walkthrough
  2. Peer review
  3. Inspection

In the second step of Static Analysis, the code written by developers is analyzed. This step helps us identify and rectify structural defects that may become errors or bugs when the code is executed.

Static Analysis helps the developer to find the following types of errors –

1. Wrong Syntax

2. Unused variable or variables with undefined values

3. Dead code

4. Infinite loops

Static Analysis is of 3 types –

1. Data Flow – Related to stream processing

2. Control Flow – Determining how the statements and instructions are executed

3. Cyclomatic Complexity – Determining the complexity of the program that is related to the number of independent paths in the control flow graph of the program

There are various other techniques used while performing Static Testing; following are some of the common ones –

  1. Use Care Requirement Validation: This technique ensures that the end-user functionalities are defined properly
  2. Functional Requirement Validation: This technique identifies all requirements for the project
  3. Review of Architecture: In this technique, all business-level processes are analyzed
  4. Field Dictionary Validation: This technique helps us analyze all User Interface related fields

Static Software Testing Process may be conducted in the following ways –

  1. Manually
  2. With the use of Automated Testing Tools

How is Static Software Testing Reviewed?

Review is the most crucial step in the Static Software Testing process. These reviews are conducted to identify and rectify any potential errors in the supporting documents. The reviews can be walkthroughs, informal reviews, technical reviews, or inspections.

Walkthrough – The author of the specific document explains the document to the team and peers. The author also answers the questions and queries from the team.

Technical Review – Technical Specifications are reviewed by the peers to ensure all the functionalities are reflected in the software and the potential errors are identified and rectified.

Inspection – A dedicated moderator conducts strict reviews to ensure that the Static Testing process is completed efficiently to make the application as robust as possible.

Informal Reviews – Informal reviewers do not follow any specific process. Co-workers review the documents and provide internal comments.


Used to evaluate the code and requirement documents, static testing is essentially used to assess the written code. Organizations incorporate static testing methodologies either manually or by automation to detect the code error early in the test lifecycle, which plays a critical role in improving the quality and reducing cost and effort.

At Yethi, we offer a thorough requirement analysis, planning/scenario design, and reviews. We ensure maximum quality at different test stages. Before executing the tests, we review business processes, products, applications, and integrations to ensure optimum test coverage. We neatly arrange the steps like reviews and analysis to execute a well-structured testing process.

CI For Automation Testing Framework

Let us consider that you have a critical project idea, and you want to set up an automation testing framework. A complex mobile application will need a lot of iteration right from the beginning. The complexities of the application may arise due to frequent changes in functionalities, adding new features, and running regression frequently to validate the changes. This will sway your project back and forth, consuming time, money, and effort, and the result will not equal up the effort made.

To end all the confusion, CI (continuous integration)/ CD (continuous deployment or delivery) is introduced at the very beginning of the software development lifecycle. The process offers a stable development environment and facilitates the automation testing framework with speed, safety, and reliability. It eliminates the challenges like lack of consistency and the numerous errors that arise due to human intervention of an application development process, ensuring that the users receive an error-free, end-product with a seamless user experience.  

What is CI/CD?

Technically speaking, CI/CD is a method that is frequently used to deliver apps to customers by using automation early in the app development stage. The main concepts associated with CI/CD include continuous integration, continuous delivery, and continuous deployment.

We can think of it as a solution to various problems for the development and operations team while integrating new code.

With the introduction of CI/CD, developers have ongoing automation and continuous monitoring during the lifecycle of an application – be it the integration phase, testing phase, or delivery and deployment phase.

When we combine all these practices, it can be called the ‘CI/CD pipeline.’ Both development and operation teams work together in an agile way, either through a DevOps approach or site reliability engineering (SRE) approach.

Automation testing in CI/CD

Automation testing in CI/CD helps the QA engineers define, execute, and automate various tests. These tests allow the developers to access the performance of their applications in an innovative manner.

It can tell them whether their app build has passed or failed. Moreover, it can help in functionality testing after every sprint and regression for complete software.

Regression tests can run on their local environments before sending the code to the version control repository to save the team’s time.

However, automation testing isn’t confined to regression tests. Various other tests, such as static code analysis, security testing, API testing, etc., can be automated.

The central concept is to trigger these tests through web service or other tools that can result in success or failure.

Test automation framework runs on a set of guidelines, rules, and regulations. DevOps team needs to implement a proper test strategy following these guidelines, rules, and regulations before they start the testing process. They have to set the process right and decide when to introduce CI during the entire software testing lifecycle, when to start the execution, and the deployment process. Some of the key points to consider:

  • Evaluating test automation frameworks: Ensuring codeless representation of automated tests, that support data-driven tests, and concise reporting.
  • Choose the test automation framework based on the requirement: The different types of test automation framework include modular testing framework, data-driven framework, keyword-driven framework, and hybrid framework.
  • Defining the objective for automation: This is an important step where the objective of the test automation must be set clear. It includes choosing the right tools, skillsets, framework, current requirements, and considering the future trends.
  • Defining the benefits of the automation framework: Considering the benefits of the automation framework for faster test script creation, longer automation span, easy maintenance, reusability probability, and good data migration support.
  • Automation compliance: Testing the software for the latest regulatory compliance.

Benefits of deploying a CI/CD pipeline in automation testing framework

Wondering why a team should work on CI/CD pipeline? Here are some of the benefits associated with it:

  • Boosts DevOps efficiency

In the absence of CI/CD, developers and engineering teams are under immense pressure while carrying out their daily tasks. It could be due to service interruptions, outages, and bad deployments.

With the help of CI/CD, teams can eliminate manual tasks and thereby prevent coding errors. In addition, it will help them detect problems before deployment. This way, teams can work faster without having to compromise on the quality. Furthermore, since the manual tasks are automated, the release rates also decrease.

  • Smaller code changes

A significant technical benefit of CI/CD is that it helps integrate small pieces of code at one time. Therefore, it gets much easier and simpler to handle as compared to huge chunks of code. Also, there will be fewer issues to be fixed at a later stage.

With the help of continuous testing, these small codes can be tested as soon as they are implemented. It is a fantastic approach for large development teams working remotely or in-office.

  • Freedom to experiment

The CI/CD approach helps developers experiment with various coding styles and algorithms with much lesser risk than traditional software development paradigms.

If the experiment does not work as expected, it won’t ever appear in the production and can be undone in the next iteration set. This feature of competitive innovation is a decisive factor behind the fame of the CI/CD approach.

  • It improves reliability

With the help of CI/CD, you can improve test reliability to a great extent. It is because specific and atomic changes are added to the system. Therefore, the developers or QAs can post more relevant positive and negative tests for the changes. This testing process is also known as ‘Continuous Reliability’ within a CI/CD pipeline. This approach helps in making the process more reliable.

  • Customer satisfaction

Customer satisfaction is an essential aspect of the success of any product or application. It is a crucial factor that should be considered while releasing a new app or updating an existing one.

With the help of CI/CD, bugs are fixed while it is still in the development phase. Through automated Software Testing for Continuous Delivery, the feedback from the users is easier to integrate into the system. When you offer bug-free and quick updates on your app, it will help boost customer satisfaction.

  • Reduces the time to market

Another essential feature that makes CI/CD popular is the deployment time. The time to market plays a crucial role in the success of your product release. It helps increase engagement with your existing customers, gain more profit, support pricing, and get more eyeballs.

When you launch the product at the right time in the market, the product’s ROI will surely increase.

These are just a few benefits of CI/CD. It isn’t just a tool for software development but also an approach to set your business as a leader in the market.


CI/CD is an essential aspect of software building and deployment. It facilitates building and enhancing great apps with faster delivery time. Furthermore, continuous testing automation enables the app to go through the feedback cycle quicker and build better and more compatible apps.

Why Yethi for your projects?

Organizations need strategies and a customized testing environment to offer continuous testing with every integration and deployment. You cannot go wrong with the implementations. Our approach towards building an automation testing framework is agile. We offer continuous testing for all your integration and deployment ensuring that you get a stable, safe, and scalable product. The robotic capabilities of Tenjin – our codeless test automation platform, which enable to learn and adapt to the application and its updates. Tenjin, is a plug-and-play banking aware solution, continuous testing, minimizing the manual effort and speed up the test execution regardless of the complexity and number of updates.

Risk-based testing for bug prevention to bug detection

The primary intent of conducting software testing is to uncover the bugs, assess them, and identify the associated risks. This approach will enhance the software cycle-over-cycle, mitigate risk, and allow smooth business operations to reflect an improved business revenue.

The testing volume increases faster than deploying the new functionalities. There is no need to test the old capabilities frequently to ensure that the new functionality doesn’t create any discrepancy in the system. Also, various stakeholders might have a different view of “risks” than developers or testers (not just probability of failure, but impact); hence, it becomes critical to carry out risk-based testing for bug prevention and detection.

Risk-based approach helps,

  • Identify high-risk areas
  • Direct testing efforts
  • Early detection for high-risk failures
  • Lower regression errors (no degradation in functionality that was working)

Testing of pre- and post-development codes help in identifying and resolving the bugs in the system; thereby, it will help mitigate risks quickly and efficiently. It is to be noted that risk-based testing is not limited to bug prevention and detection alone. After the complete code of the software is written, the testing experts can also identify issues based on their expertise, knowledge, and experience when the software is in the development or designing phase. However, no software should go without risk-based testing in the deployment phase, as it can cause technical issues or corrupt the database and applications.

Difference between Bug Prevention and Bug Detection

Bug prevention and bug detection in software are two different constraints with regards to the aspects of before the code is written and after the code is written, respectively. Bug prevention is the practice of discovering issues before the coding for any software is completed. With bug prevention, concerned individuals can rethink the design so that the code possesses the ability of risk mitigation.

On the other hand, bug detection is the practice of uncovering unknown risks during and after the code is written concerning the impact of other distinct constraints on code. Through bug detection, coding teams can make changes in real-time to enhance the scope of software utilization and avoid any probability of encountering issues.

Concept of Risk-Based Testing – bug prevention and detection

Risk-Based Testing can be explained as a basis of prioritization of the test cases that are to be conducted on software. By documenting the significance of function, its likelihood of failure and impact in case of failure, testers can focus their efforts on areas that can have a significant negative impact.

The process of bug detection comprises analysis, prevention, and management, which will ensure that all the bugs and defects are identified and resolved before the software reaches the final users and prevent it from causing any issues in their system.

Further, bug/defect analysis, prevention, and management practices ensure that all the bugs/defects go through a pre-determined life cycle to be fixed and closed. The nature of the bug depends upon the resources it uses, and the effects cause the software to behave abnormally. The goal of bug analysis, prevention, and management practices is to identify the root cause and treat them. 

The root cause of the bug occurrence generally contributes to the factor of the bug. It needs to be mitigated and resolved to eliminate all the probability of recurrence of the concerning defect. However, the coding team needs to make sure the elimination of root causes should be affecting the performance of the software in any way.

The bug prevention and detection in the risk-based testing process concern the risk containment and mitigation aspects for the risk management process. The risk management process ensures that software is prepared to mitigate the risk whenever it arises during the risk-based testing process. It is based on predetermined programming that can minimize the adverse impact.

Risk Monitoring and Controlling

Risk monitoring and controlling is the process of tracking all the identified risks, such as monitoring residual risks, detecting the new ones, assuring risk plan execution, and evaluating the software ability and effectiveness to eliminate the risks. The risk monitoring and controlling process works throughout the software development life cycle by recording the risk metrics related to the implementation of contingency plans.

While carrying out risk-based testing, 75% of risks arising in test cases can be monitored and controlled, whereas 25% of risks in the test cases may remain undetected due to lack of exposure to application functionalities. Risk monitoring and controlling is a continuous process as new risks may arise by adding new functionalities in the ongoing software development lifecycle. An efficient risk monitoring and control process aims at providing necessary support. It ensures that all risk-based testing practices and robust communication are adapted for making effective decisions to mitigate risks proactively.

Overall, it can be stated that risk-based testing and its varied practices and processes ensure that software is deployed for use by the final users without any bugs or defects. Risk-based testing carries out the practices for bug prevention, bug detection, defect analysis, defect prevention, and defect management for eliminating every possibility of software misbehavior at the user’s end.

Risk-based testing also documents every risk and its triggers so that a risk mitigation plan can be executed as soon as any risk occurs, or trigger is activated. Risk-based testing works in real-time as it starts with the planning phase of software and ends when software is deemed ready for deployment after all the testing. Real-time working of risk-based testing ensures that all the bugs and defects are eliminated from the root causes before they adversely affect the performance of the software at the users’ end.

Yethi is your go-to all your software QA needs

Even a minor bug can adversely affect the software quality putting the brand reputation at stake. An excellent testing process can improve the quality of the software. At Yethi, we follow a process of risk categorization and prioritization. We offer automated business process simulation for high-risk areas to increase the efficiency, accuracy, and consistency of the banking/financial software.

We select test scenarios based on importance to customer & security, financial impact, the complexity of business logic, and integration points. Being a leading QA partner for banks and financial institutions, we have touched base in over 22 countries offering QA solutions for more than 80 clients worldwide.

Yethi’s test automation platform, Tenjin, is a 5th generation robotic platform that can efficiently carry out even the complex testing process with ease. It handles test execution, test management, and defect management at various stages to ensure accurate test results with excellent performance without compromising the critical aspects.

What Are the Different Types of Performance Testing?

Organizations determine various performance-level benchmarks for systems, transactions, infrastructure, and applications. They understand that minimized time for page loading, lower response time, and seamless navigation can more deeply satisfy customers. But there is so much that goes on beneath to maintain the level of performance. One of the key pre-requisites for launching a software application is to check the page performance concerning speed, scalability, and stability under high traffic conditions.

In extreme scenarios like high user-traffic hours, the organization must maintain the page loading speed, application sustainability and stability of their applications. Because even a stable website or app can experience performance failure or crash during extreme loads. Such fails may occur due to ineffective processing, memory over-utilization, poor network, or lower data transfer rates. Hence, performance testing is a critical step that can yield positive business outcomes and offer a seamless user experience.

Types of Performance Testing

Performance testing is conducted to check if the application is performing flawlessly under all load conditions, and not performed to identify bugs. It is used to check the speed, scalability, sustainability, and stability of the application. Here are the different types of performance testing you can run under different conditions.

Load Testing

Load testing is used to test the system performance for a constantly increasing number of end-users until it reaches its threshold value. Load testing is performed to determine the response time, identify the threshold value, and measure data input rates. With these data, we can determine the point at which the application breaks and can fix the load issues before launching the product.

With the evolving digital trends, the number of digital users is also constantly increasing. It becomes essential for organizations to test real-world load scenarios to ensure the application works well even under peak visitor hours. It is also performed at the hardware and software level to measure the systems’ ability to scale up and down with a request in the number of users and other similar parameters for measuring system performance. This aspect is also referred to as scalability testing.

Advantages of load testing:

  • Load testing can determine the operating capacity of the application and scale up to maximum under heavy user load determining end-user experience
  • Load test gives an idea of the real-world user scenario and helps to fix any performance-related issues before the application is being launched.
  • Application downtime can leave end-users frustrated, which may even lead to losing them. Load testing helps find a solution to these real-life scenarios.
  • Helps in taking advanced corrective measures and solving the issues for better scalability
  • Load testing helps to identify the performance concerns before the product launch; hence, it saves costs arising due to post-launch failures.
  • Determine the limitations like response time, network, CPU usage and more for the web application under test
  • Identifies the root cause of various application performance issues
  • Helps in the tracking of effective tool utilization

Soak Testing

Soak testing, also known as endurance testing, is performed to identify the continuous load an AUT (application under test) can withstand within the determined time. It is used to determine the response time and stability and check how well it performs under heavy load for a pre-determined period.

Advantages of soak testing:

  • Determines the application suitability under a certain environment
  • Determines if the system is sustainable and capable of running overtime
  • Detects errors and bugs that go unnoticed during other performance tests
  • Detects performance decline due to high and continuous performance load
  • Helps in improving the performance issues and monitor overall application health
  • Improves infrastructure requirements of customers with the help of test results

Stress Testing

Stress testing is a form of intensive testing that can determine system stability while testing its performance beyond standard capacity. Stress testing is used to analyze the system behavior after failure; hence, it is also called recoverability testing.

Advantages of stress testing:

  • It is used to determine the threshold limit, i.e., the safe usage limit
  • It is used to determine the recoverability after a system failure
  • It is used to confirm if the intended specifications are met
  • It is used to determine the system stability

Spike Testing

Spike testing is done to test the application for unplanned and unpredicted increment and decrement of load. In this testing, the system is loaded and unloaded unexpectedly. In spike testing, the systems are tested to check their performance in case of a sudden rise or decrease in the number of users.

Advantages of spike testing:

  • It is used to identify the intended load above which the system can perform
  • It is used to determine the consequences arising due to unexpected spikes in end-users
  • It can avoid application breaking during an unexpected rise in the users beyond maximum levels
  • Prepares the system for real-world scenarios
  • Prevents the system from crashing

Volume Testing

Volume testing is executed to analyze system performance on the increase of volume of data. Usually, the volume of data is determined at the beginning of a project, but there may be a sudden surge of data. Volume testing, which is also known as flood testing verifies that this undulation data does not hinder the application performance.  

Advantages of volume testing:

  • Detect issues at the early stage to improve customer satisfaction with increased stage
  • Identify failures arising due to data volume before the users use them and reduce the system maintenance
  • Ensure that the data are stored in the correct format, also prevent loss of data while updating a large amount of data
  • Prepares the system regarding the data volume
  • Identify high volume system data areas that reduce system response time
  • Ensure that the system works effectively in the real world with a high volume of data
  • Test the system capacity concerning data volume
  • Reduces the overall risk of system performance failures

Failover Testing

Failover testing is performed to verify the capacity of the system to assign extra resources and provide a system backup for operation in case of server failure for any reason. Failover testing focuses on critical applications only rather than disrupting the full stack.

Advantages of failover testing:

  • Prepares computer to run mission-critical programs
  • Switch easily to system backup when the primary system fails with continuous performance
  • Helps in business continuity while the IT team resolves the issue

Following are a few more testing methodologies for an extensive performance testing process

  1. Availability testing

Availability Testing is conducted to collect failure events and repair times for an application over a period. It helps compare the availability percentage of server backup based on the service-level agreement.

  • Configuration Testing

Configuration Testing is conducted to validate the software application with various combinations of hardware and software to determine the functional requirements. It helps find the optimal configuration under which the software application performs without flaws.

  • Testing System Resilience

Testing system resilience is critical as it validates that the systems have the capability to absorb the impact of the problems while recovering from the issues to maintain an acceptable level of performance.

  • Performance Compatibility Testing

Performance capability testing is conducted to evaluate the performance of the system across different browsers, databases, operating systems, networks, and hardware.

Performance testing by Yethi

Yethi’s service level agreement is based on the performance level benchmark pre-defined by our clients. To fulfil these benchmarks, we simulate the real-time systems to ensure that your application, transactions, and modules perform at their best even during volume increase, load on systems, different configurations, systems availability, and more. We follow a strategic performance testing framework and validate your system performance against various criteria.

Yethi is a niche QA service partner for global banks and financial institutions that offers efficient end-to-end testing. We analyze different transactions based on the requirements and execute testing for applications-under-test and servers-under-test. From test creation for end-users to monitoring key performance indicators and execution of performance testing, Yethi carries out all aspects of functional and non-function testing with nearly 100% accuracy.

Importance of Automated Regression Testing

As technology is advancing, the software gets subjected to various new and improved features. Such integrations may cause errors/bugs in the system not allowing it to function accurately. Hence, regression testing is conducted to test the entire software to understand its behavior upon the addition of new integrations and identify any bugs arising due to the same. This is true for even minor code changes or any alterations made across the process. Simply put, regression testing ensures that the software or the piece of code that was previously developed and tested still behaves in the same way after the code has been changed or altered.

Carrying out regression testing manually can be a tedious task, and due to its mundane and repetitive nature, manual regressions may not be fruitful. Hence, regression testing is automated to ensure consistency and accuracy while avoiding human errors.

Significance of Automated Regression Testing

Incorporating manual regression testing can be a draining experience as it involves a lot of time and effort. Further, its tedious nature is prone to causing high errors. With the ever-changing technology, the process is getting complex and manually handling regressions cannot be considered a feasible option. Including automated testing as a part of the product development strategy is what most organizations are doing today.

Automation testing yields the best outcomes with optimal time and resource requirements. It focuses on conducting accurate regression to create products of higher quality, which in turn will offer a seamless customer experience. It streamlines the process, improves workflow efficiency, delivers the effective solution, and speeds up turnaround time.

Benefits of implementing automated regression testing:

Saves Time and Effort: Automated regression testing can handle repetitive tasks effortlessly and efficiently in lesser time, hence, saving significantly on time, cost, and effort.

Reliability: Automating regression testing will reduce human errors considerably while ensuring accuracy and consistency on the outcome. Their accurate and consistent nature makes the process reliable compared to manual regressions.

Tests running round the clock: One of the major advantages of automating regressions is that tests can be initiated and executed any time, i.e., tests running 24/7 and results being generated constantly.

Cost-effective: The reusable nature of test cases significantly reduces the cost of test case generation, making the whole process cost-effective.

Improved ROI: Automating regressions may seem to be a little more expensive than including expenses for buying tools, initial setup costs, and investing in writing test cases. However, this maybe a one-time investment; it yields good results in the long run adding to improve ROI metrics.

Early detection of bugs: Testers will be able to spot problems and defects earlier in the software development cycle thanks to automation.

Steps involved in Automated Regression Testing

Choosing the suitable test cases

Choosing which tests to re-run for regression testing is a combination of technology awareness, clarity on requirements, and intuition. Whether you’re performing priority testing or subset testing, the goal is to increase the likelihood of triggering any regression that has been introduced. Choosing the right test case from the repository is the most critical step that determines the success/failure of the testing process. Choosing the right test case is an indication that half work is done successfully, the rest remain in executing it with the right tools.

Regression test execution

Before the advent of autonomous testing, ensuring that your tests are effectively scripted is a prerequisite for good regression testing. If a test requires the system to be in a specific state, try sequencing tests to reduce the number of times you must change the state. Make sure your test suite produces data that is straightforward to understand. It should be simple to figure out which cases were unsuccessful and what the system was up to at the time. Occasionally, you’ll see apparent failures resulting from incorrect configurations.

Maintaining regression tests

Like any other tool, automated regression testing is only as good as the people who use it. And, like any suitable instrument, it needs to be cared for and maintained. When new test cases are produced, consider whether they should be included in the regression tests. “Does this bug need to be added to the regression testing?” you should ask yourself whenever you patch an actual bug in your code. In most circumstances, the response will be “Yes.” You should, however, include tests that check the functionality of any new code paths.

Why Is Automated Regression Testing Right for Your Project?

Organisations build software applications to provide value to the customers. With time, these applications need change, or the developer may look to add more functionalities and features to the software based on the customer requirements. With each change in code or functionalities, the app becomes more and more complex. Hence tests for regression issues should be added more frequently with every update. Automated regression testing could be a boon for such organisations.

Here are some of the reasons why automated regression testing could be suitable for your project:

  • get higher test coverage
  • get continuous results
  • higher test efficiency
  • fast results
  • reusability of tests

Yethi for Automated Regression Testing Solutions

Yethi is the market leader in offering software QA solutions to global banks and financial institutions. Yethi’s test automation platform, Tenjin, is capable of handling efficient regression testing for complex banking and financial system. It has proven to offer nearly 100% accuracy in regression scenarios, and its half-a-million test case repository cuts immensely on the cost.

Tenjin is a 5th generation test automation platform with robotic UI capabilities which can automatically learn and relearn without manual intervention. It offers high test coverage and has the ability to test even the complex banking/financial system with utmost ease.

Shifting to UI Automation Testing

As the digital space is evolving at a tremendous speed, the use of digital devices has also witnessed immense growth. Digital devices like laptops and mobile phones have become a significant part of our daily lives with almost 80% of the world population using them. Hence, when an application is developed, either mobile or web, it should offer a great user interface (UI) as it forms the first point of contact with the end-users. If the app fails to create a first great impression, chances of the users not exploring the other parts of the app becomes high. This is one of the reasons why organizations are investing in UI testing to ensure they offer a seamless user experience. UI testing which was earlier conducted by the manual approach has now shifted to UI automation for better outcomes.

UI testing automation increases brand value, reliability, and time-to-market while reducing cost. Moreover, the process of execution is easier, more efficient, and less time-consuming when it is automated. Let’s understand UI automation better and explore its benefits and future scope.

What is UI Automation?

User Interface is considered to be the face of an application that creates the first best impression among the users. If the UI fails to connect with the end-users, it can completely break the brand. Hence, it is important to test the UI thoroughly to offer an exceptional user experience. Manual UI testing is often found to give inconsistent results due to its tedious nature. However, shifting to UI automation has proven to give accurate and consistent results while saving on cost, time, and effort.

UI automation is basically the automated process that is conducted to test if all the parts of an application’s front-end work as expected. UI automation testing provides an elaborate report on the end-user interface performance by checking if the application is running correctly and keeps a track of simple interactions or by simulating real user requests. Here, the test scripts are written to automate the execution of the tests. This technique allows the process to be controlled through software code instead of testing it manually.

Why should you consider UI Automation Testing?

The UI automation testing process is conducted to effectively test the application’s interface for its features and performance. It is often considered an end-to-end approach to testing as it can:

  • simulate and test the behavior of the application’s users by acting on the computing system’s interface with simulated user input
  • automate all testing operations for the software programs
  • incorporate user interface testing into the development process
  • can submit test results and generate reports.

Benefits of UI Testing

Benefits of UI testing includes:

  • Automated tests are useful for teams running on agile software development workflow as good test coverage rates can be achieved by it
  • Well-tested code makes it easier to find and fix bugs faster
  • Once the automated tests are set up, they can easily be reused; this makes the whole process cost-effective
  • Automated tests run multiple folds faster than manual ones
  • Automated tests are more accurate than manual testing.
  • Human errors can be easily avoided in automated testing
  • They’re cost-effective and time-effective

Why is there a shift to UI Automation?

Developing a product can be challenging and it isn’t always easy to determine the best way to test the developed product. Testing is a crucial part of the entire product deployment cycle as it ensures the quality of the product is top-notch before it reached the end-users. Though there are manual and automated testing processes, it is important to understand both of them before you decide to choose the one that works for you.

Manual UI Testing

In manual UI testing, testers prepare test scripts manually and run individual UI scenarios inside the application. It involves scripting actions or inputs that lead to specific outcomes in order to verify a user’s experience. Since it requires a lot of manual effort, the process gets mundane and tedious giving rise to errors. This is a cumbersome process involving a significant amount of time and effort.

UI Automation Testing

UI automated testing is a valuable tool when it comes to developing software tools or applications. This type of testing relies on pre-programmed scripts that are frequently called tests or test cases. These tests tell the program what to expect under different UI circumstances. Automated software testing provides a repeatable process that allows developers to thoroughly cover every part of their codebase. Automated testing can work with each iteration to determine whether certain elements in an application need attention or revision.

Why UI Automation Testing over Manual Testing?

  • Manual testing takes time and cannot keep up with several development cycles, while automation can effortlessly identify errors without human intervention
  • Manual testing is time-consuming and expensive, while automation testing involves lesser time and effort
  • When conducting repetitive tasks, manual testing is more prone to errors due to its mundane nature. Automation, on the other hand, minimizes the likelihood of such errors
  • When executing complicated iterations, manual testing is difficult to rely on. However, automation testing offers accurate and consistent results under all circumstances

UI Automation Testing Tools

UI automation testing is a complex task, which depends highly on the tools and techniques that are used. Though there are plenty of tools available in the market, one cannot simply rely on a random tool. Proper research can help one to pick the best tool for automation testing based on their requirement, which will make a difference to the project in the long run.

Here are some key points to consider while comparing automated UI testing tools so you can make the best selection:

  • Building and maintaining test scripts is straightforward
  • Allows seamless entry of huge amounts of test data during load testing
  • Non-technical people may easily execute test suites
  • It offers an extensive reporting facility
  • All UIs are supported – web, desktop, smartphone etc.
  • For versatile test script development, a wide range of languages is supported
  • For automated builds or deployment, seamless connection with other tools inside the CI/CD pipeline is expected
  • Easy maintenance
  • Modifications to pre-existing scripts are simple to implement
  • The ability to test complicated user interface elements
  • Affordable pricing


Test automation is a way to quickly and efficiently ensure that the user interface of the application is performed throughout the entire testing cycle. Although setting up automated tests might require extra effort at first, it is proven to be easy and effortless in the longer run.

UI testing forms an important aspect of the overall software testing process. A good UI will help retain the existing users and provide scope to attract new users too. An impressive UI will help the organization to build brand credibility, create a loyal customer base, and generate good business revenue. Hence, automating UI testing will help organizations to improve their business like never before.

Performance Testing in Agile Environment

Performance testing is a critical part of any testing strategy as it indicates the maximum user load the system can process, thereby, helping to mitigate the associated risks. It won’t be wrong to state that good performance of the application alone can help you stand out in the market. With the increasing focus on performance, organizations are moving their testing strategy from traditional approach to agile methodologies for creating successful products.

Conducting performance testing in an agile environment has its own benefits. Agile environment improves the application performance testing by executing tests on continuous integration and continuous delivery simultaneously, which is otherwise difficult with the conventional approach. It helps organizations develop higher quality software in less time while reducing the cost of development.

What Is Performance Testing? The Need to Test It in Agile Environment

With the increasing trend of digitization, the use of websites and mobile apps is increasing. Popular apps and websites like Netflix, Google Pay, etc., have millions of users all at the same time. The load created during the peak traffic period is immense; in case, the system fails to keep up the load, it can disrupt the business. To ensure that business continuity is uninterrupted while offering a seamless customer experience, even during unrealistic traffic, performance testing is conducted. Performance testing creates reliable software applications with great speed, stability, scalability, and responsiveness. It is one of the important criteria directly related to the user experience.

Organizations are adapting to creating new software in agile environment to improve the process, promote change, and embrace innovation. The agile environment offers a flexible space for the organizations to improve the process by emphasizing on the working software, developer/testers, customer collaboration, and responding to the changes. When performance testing is carried with the agile approach, it helps to deliver quicker results with better ROI.

The prime approach of using performance testing in an agile environment can be understood by considering the complete software development project. Moreover, the automation test scripts to run performance testing lets the organizations develop high-quality software in a lesser time frame with reduced developmental cost. It mainly focuses on testing the performance in the early stage of development and testing. Looking at the advantages offered by performance testing in an agile environment, performance testing gets consideration in the complete agile SDLC process. It also helps in testing the application behavior under heavy load.

Critical Considerations for Running Performance Testing in Agile Environment

When conducting performance testing using agile testing methodology, the application testing is conducted in smaller cycles. As a result of this trend, with every iteration, the application gets better than the previous release. The process is streamlined and also allows making any further change or addition of new requirements anytime. Key considerations include:

  • Having a clear vision of the expected result is critical. Having a clear context set for the project will help you determine the further requirements such as building architecture, implementing new features, setting the timeline, and determining the scope of performance testing
  • Determining the reason for performance testing by observing the trends in resource usage, checking threshold, responsiveness, and collating the data to plan for the required scalability
  • Creating a strategy to incorporate performance testing value additions like integrating external resources, emphasizing on the concerned areas, checking the load range etc.
  • Deciding the tools and resources to be used for syncing up with the test environment
  • Identifying and executing the tasks are of highest priority criteria to decide the performance of the system
  • Another important consideration involves creating and analyzing the report to check if the outcomes are as expected

Resolving Performance Issues in Agile Environment

To get maximum efficiency under an agile environment, one should identify and resolve the performance issues in the base code to avoid further bottlenecks. There are three stages to consider while resolving performance issues:

  • Optimization: Tests should be implemented at the base level to avoid issues at a later stage
  • Component Testing: It removes defects at the application component level
  • App Flow Testing: It helps to test app flows that determine the UX consistency for varying loads

Different Factors That Affect Performance Testing Within Agile Environment

A performance tester gets involved from the beginning of the sprint so that quality products can get assured by the end of the development cycle, and delivery within the estimated timeline. Below are the different factors affecting the performance testing process:

  • Non-availability of trained resources for critical projects
  • Unavailability of flexible tools for performance testing
  • No prioritization of performance testing to take care of performance defects
  • Performance testing criteria might not be planned for every sprint in the case of some agile projects

Advantages of using Performance testing in Agile Environment

Performance testing in agile Environment has proved to be helpful for all organizations; its benefits include:

Capacity Management: It helps determine if the current hardware can handle a specific amount of traffic by identifying the capacity and size of the server required. It also helps in saving the investments made on private Cloud.

Testing Speed: It can be determined by mimicking the multiple scenarios and then testing the reactions of all those paths under different situations. In this way, all the significant flows and the user journeys can get tested for an application, even the unknown cases.

Increased Team Efficiency: Agile follows detailed planning and documentation, which can help in making the development process efficient and faster. It also helps in fixing the issues at a very early stage during development.

Competitive Advantage: These days, the end-users have a low tolerance for performance issues and bugs. Performance testing proves to be helpful in having a higher retention rate and demonstrating the company’s competitive advantage.

Yethi’s Performance Testing to Offer Seamless Experience

Yethi is a QA service provider to banks and financial institutions across the world. Highlighting Yethi’s performance testing process, our test automation tool, Tenjin, conducts the test efficiently to eliminate any performance issues and ensures that the application works at its best. It monitors and handles the test to check the response time, speed, scalability, and resource usage under the standard workload, thereby, creating a robust and scalable system that works without any disruption.

Yethi has helped several global banking/financial institutions with an easy and efficient test automation solution. Our revolutionary solution has changed the course of test automation by providing nearly 100% accuracy.

How does test automation vary between development and acceptance in BFSI industry?

Test automation has transformed the core software system of organizations with a better and smarter workflow approach. The improved test automation helps to optimize the entire process, thereby, eliminating any operational gaps and offering a greater level of customer satisfaction. Test automation plays an integral part in the highly complex banking and financial sector where the process involves extremely sensitive financial data, which offers NO scope for compromise. Being popularly used in banks and financial institutions, test automation helps to reduce time and effort on repetitive jobs and increases the speed of delivery multiple folds when compared to manual testing.

Though test automation has eased the tedious and time-consuming manual software testing, its success depends only on the efficiency of automation tools being used. Adding to the sensitive data-driven and multi-layer workflow of the banking and financial sector, a perfect automation tool is required that will align with the organization’s core software system and deliver favorable outcomes. The test automation requirement varies between the development and acceptance phase in the BFSI industry, let’s discuss it in detail.

Test automation in the software development cycle

Testing in the development phase involves a series of to-and-fro cycles to ensure that the newly developed software is working without any defect. The entire cycle of software development or sub-development phase requires a specifically designed test automation tool to get the software immaculately working. Further, with the introduction of more agile DevOps processes, testing is carried out earlier in the development cycle to ensure the developed software is of higher quality. Additionally, continuous testing process is also introduced to execute the automated tests as a part of the software development pipeline to increase quality and reduce business risks.

Software development cycles in the banking processes involve critical data such as an individual’s financial information, transaction history, and personal details. To safeguard the crucial client data and have a fully functional yet completely secured banking software, it is important to have a strong testing procedure in place.

performance failure, security breach, or a poorly functioning system will lead to loss of potential and prospective clients, eventually incurring a huge financial loss. Organizations need to understand that it’s equally important to invest in high-quality, fully functional test automation tools to give the best service to their clients.

In this era of growing dependency on digital platforms, only a good testing system has the power to make or break your business. Poorly performing testing systems can compromise on the performance and security, leading to highly dissatisfied customers, which can eventually shatter the brand within no time. That’s why, we at Yethi, have introduced an efficient test automation platform for banking and financial businesses to work at their best while offering complete peace of mind to the entire client base. Tenjin, Yethi’s codeless automation tool, has revolutionized test automation in the banking and financial sectors, offering an impeccable system that offers no scope for errors.

Yethi has established itself as a market leader in QA services to the BFSI industry by offering testing solutions to popular banking software including Oracle FLEXCUBE, Infosys Finacle, and TCS BaNCS. Tenjin has created a deep impression in the market for its quick deployment test automation solution that conducts the testing without the need for scripts or codes while offering nearly 100% accuracy.

Test automation for software acceptance

Banking and financial systems are constantly modifying their core software to add new features or upgrade the existing ones to meet the ever-changing demand of the customers. Testing associated with the adding of a new feature to cater to the company/institution’s requirement is defined as acceptance testing.

User acceptance testing forms a vital part of the software development life cycle as it is tested for real-world usage for the intended audience. Otherwise known as UAT (user acceptance testing), it is done when the software has undergone integration testing, unit testing, system testing, and other functional testing aspects. This testing is the final stage of functional testing to check if the final results are accepted by the end-users.

To ease the acceptance testing from a manual approach, test automation tools for acceptance are being used popularly by banks and other financial companies/ institutions. Manual test execution takes time as the test codes are manually written and reviewed by the testers. Such an approach is not suitable for a highly agile working system that is followed by companies today. To keep up with the trend and offer modern solutions to new-age problems, Yethi offers automation for acceptance testing.

At Yethi, we understand how essential it is to decide and use the right automation tool for testing user acceptance of the banking/ financial software. Yethi’s test automation tool, Tenjin, is a codeless platform that is designed to rapidly scan through the software and detect any defects. It improves the application quality by fully investigating the formal expression of your business needs and addressing any operational and infrastructural gaps. Tenjin is one of its kind of tools that can offer testing of banking/financial software with minimal human interference and nearly 100% accuracy.

The future of test automation in banking/ financial software

The next wave of artificial intelligence (AI) and machine learning is already taking over all the technological processes across various industries. The incorporation of these technologies has been a crucial part of the banks and financial companies/ institutions, as the number of account holders is constantly increasing. It becomes important for the banks to consider the need of the current tech-savvy millennials while keeping things simple for the previous generation.

Banks and other financial companies are creating and updating software for online, mobile, and other digital platforms. This increasing number of online users has created a need for an immensely effective software testing solution that will leave no scope for compromise in any aspects of functional usage, performance, or security.

The future of test automation in the BFSI industry looks quite promising with the growing usage of digital platforms. The sector has already seen the integration of AI, machine learning, and robotics; however, the future looks different with advanced robotics, augmented reality, and smart machines being used in a common, real-life scenario. The evolving banking/ financial process will further require an advanced testing solution. The future might see robots take over the testing process or a more agile process might come into the picture that might offer impeccable execution. Technology is evolving at a faster rate than we can imagine, so the future will see advancements much beyond our current understanding.

Testing & Quality in Continuous Delivery, DevOps, and Observability

In today’s fast-paced world, development and deployment must go hand in hand to ensure timely delivery without compromising on quality. To support this modern application development approach, continuous delivery is implemented, where the code changes are automatically prepared and deployed for production. But often, when the development and operations are not managed well can lead to failure in the production of the application. To resolve this issue, DevOps comes to the rescue, it eliminates the conflicts and creates the perfect environment for building sustainable applications.

Deploying DevOps models is an integral part of the process that accelerates software deliveries while assuring a high-quality deliverable. To streamline the entire process and understand the success or failure of the process, it is important to establish continuous monitoring and observability. The observability process allows to collect the metric and decide on the next actional steps to be taken. Hence, DevOps and observability are essential criteria when it comes to testing and maintaining quality in the continuous delivery pipeline.

DevOps test strategy: The need for continuous testing in continuous development

Organizations are adopting the DevOps approach to develop software that streamlines the entire software development and delivery lifecycle. DevOps strategy involves implementing agile practices of continuous integration (CI) and continuous delivery (CD) to ensure an easy and efficient result. The introduction of continuous testing verifies the operational structure, detects errors early, and resolves conflicts as soon as it is identified.

The goal of CI/CD and the associated continuous testing process in the DevOps methodology is to evaluate and eventually improve the quality of the process. Here, the testing, operations, infrastructure, QA, DevOps, development, and testing are interconnected. The effectiveness of the final result depends on these parameters.

How implementing continuous testing helps in the continuous delivery pipeline

  • It helps detect defects earlier, which eventually allows the company in reduced cost and improve quality
  • Continuous testing in quicker deployment
  • The automated testing system helps reduce the manual effort and improves the consistency and accuracy of the end results considerably
  • Since the testing starts at the early stage, it ensures a better test coverage
  • With better coverage and accuracy, application-related risks can be mitigated quickly
  • The transparency of the test results helps the developers to improve the software by implementing different techniques

As a part of the testing strategy, organizations are also investing in good DevOps tools. Some famous DevOps tools can be version-controlled source code managers like GitHub, GitLab etc. Organizations can also consider CI/CD pipeline engines to validate and deploy the application to the end-user during the development lifecycle. Using integration and delivery tools are a great help to solve problems.

For example, Cloud environments allow using Cloud resources to automate the deployment. As-a-Service models like SaaS, PaaS, IaaS allow the set of required resources to flawlessly generate code, test the code, and maintain the code.

Monitoring the progress is also a significant part of the development cycle. The code creation and security checks are significant parts of monitoring.

The need for observability in the CI/CD pipelines

The evolution of workflows to CI/CD approach is carried out in the advanced DevOps environment has proven to improve the quality by multiple folds. However, as the advancement progresses, they get associated with a new set of challenges. In order to mitigate any known or unknown risks, it is important to carefully analyze and control the process. The analysis metrics will help the teams to measure the success rate; this is done by implementing Continuous Monitoring and Observability process.

Advantages of continuous monitoring and observability

Vulnerability checks: When a new code is introduced in the system, it is essential to check what security vulnerabilities it can cause. It is important to implement constant observability to check the way the code is performing, any data leaks, or unauthorized activities. Continuous monitoring and observability will have a check on all possible threats and keep the team prepared to mitigate any kind of risk.

Understanding future trends: By implementing constant monitoring and observability, the organization can analyze the infrastructural and operational gaps. The metrics will help the organization to understand the future scope and build a solution to resolve the issue.

Reviewing the analysis: Continuous monitoring and observability allows the developers to have an elaborate result of the working of the system. Any discrepancy can be easily identified during the general observability process and given an opportunity to fix them before deployment.

Long-term analysis process: A similar QA process may not be feasible for testing different workflow systems. Hence, we cannot conclude the working of a certain process as a success or failure. On implementing a continuous monitoring process over a longer period of time, the process can be reviewed based on the data.

Ways to implement monitoring and observability

By implementing Monitoring and Observability in the production environment, the following can be achieved.

  • Help in getting prior indications regarding service degradation or outage
  • Easily detect unauthorized activities and bugs to resolve at the earliest
  • Identification of long-term trends is crucial for an organization. Monitoring and observability help organizations to find trends for business purposes and planning
  • It will help the organization to know the unexpected side effects of new functionality or changes.

Why is Yethi your perfect QA partner?

To achieve long-term success, installing tools is not sufficient, you need new ideologies and continuous support to succeed. Yethi is your perfect QA partner for helping you achieve your business goals. Having helped more than 90 customers across 18+ countries, we have emerged as one of the leading QA service providers in the BFSI industry.

Our test automation platform, Tenjin, is a 5th generation robotic platform that has a simplistic plug and play design. It can offer high test coverage with an end-to-end testing approach, and is capable of testing even the complex software system with utmost ease. Tenjin supports end-to-end testing and offers detailed metrics with its TTM (Tenjin Testing Management) solution.

Emerging Trends in Performance Testing

Creating a visually appealing website with seamless functionality is great, but if it crashes easily or fails to work under higher traffic, it can never be a successful one. Hence, performance testing is a crucial parameter when it comes to software testing. It gives a clear picture of how the website/ application is performing in terms of speed, thereby, offering scope to increase its robustness and reliability.

Performance testing is a rapidly developing field and has witnessed enormous advancements, especially in the recent years. Teams are trying to move to quicker, cheaper, agile, and more accessible methods to improve the performance testing process.

Like the previous years, this year too will witness new trends in performance testing that will enable more responsive development in shorter spans with fewer risks factors. The emerging trends in performance testing are discussed here in detail.

Latest trends in performance testing

The new trends in performance testing are still at a nascent phase and will make their presence in the market much sooner than we anticipate. Here are some of the popular testing trends that will transform software QA in the near future.

Artificial Intelligence

The use of Artificial Intelligence (AI) in performance testing for websites and apps is not new. AI automation is slowly making its presence as a go-to option for testing and QA teams at every stage of performance testing.

The use of artificial intelligence in performance testing for websites and applications is expected to grow further in the upcoming years and become a significant trend of all time.

Internet Of Things Testing Market

The Internet of Things (IoT) has seen rapid growth in the last few years, and this growth is expected to continue in the future too at a larger scale. This means that there will be millions of devices operating in various unique environments. Testers will face new challenges to ensure that the testing cycle, performance, and security aren’t compromised. To mitigate these risks, testers will have to adopt an IoT-focused approach, leading to the rise of Cloud-based and IoT testing environments.

Cloud-based Testing

Cloud computing services are becoming popular for functional and non-functional software testing. There are a plethora of benefits of using Cloud-based tools for performance testing. Some of them are:

  • High Scalability: With a Cloud-based platform, unlimited users can carry out performance testing simultaneously.
  • Low Cost: It allows on-demand resource provisioning for performance testing for websites and software without the need of building infrastructure, thereby, helping reduce performance testing costs.
  • Supports Production Environment Testing: Generally, traditional, older tools allow performance testing only in the test environment. However, with Cloud-based tools for performance testing, the testing can be carried out in the production environment as well.

Open-source Tools for Performance Testing

Open-source tools promote collaboration by giving testers the ability to view and edit the source code. This leads to the team working efficiently and helps create a better product while reducing the production cycle time. Additionally, they also provide an easy learning platform for new testers. No doubt that open-source performance testing tools have become quite popular in the testing community and will remain an integral part of it.


DevOps is a collaborative approach combining Development (Dev) and IT Operations (Ops). It involves all the stakeholders in the software development process until the product is delivered to the client. DevOps aims to reduce the software development life cycle while delivering high-quality end-products to the client. To accomplish this, DevOps involves a highly interconnected, collaborative, and agile approach. Looking forward, DevOps seems to be the go-to approach for many organizations due to the various benefits it delivers.

Production Testing

Another emerging trend in performance testing is testing the software or website in the production environment. Generally, performance testing is done in the development, staging, and pre-production environments. However, in production testing, the new code changes are tested on live user traffic on the production software itself.

Production testing allows only a small set of users to be exposed to the software. The testing team then carries out performance testing for websites or applications and rolls out new features to check user responses. They can verify whether the software or website works as intended or not. Some of the techniques used for production testing include:

  • A/B testing: Testers can compare two versions/features at the same time to see which one provides a better user experience.
  • Blue-Green deployment: It involves running two production environments that are as identical as possible. It helps reduce downtime and risks as it enables gradual and safe transfer of user traffic from a previous version of the app or software to the new one.
  • Security Testing: Data threats and attacks have increased in the last few years, resulting in tangible and intangible losses for every party involved. Thus, every stakeholder, including businesses, has realized the importance of data safety. Testing teams, too, have prioritized security testing in performance testing to avoid any undesired instances. The threats are expected to only increase as we steadily move to a more interconnected world. That is why software testing teams must become competent to detect and neutralize threats at the earliest.

Behavior-driven development

Behavior-driven development (BDD) is an agile approach that encourages collaboration with shared tools and processes to create a mutual understanding between testers on how the end-product will behave. In BDD, the testing team needs to build test cases based on user behavior and interactions to create a high-quality end-product. BDD is expected to gain further prominence as AI goes mainstream in performance testing.

These are the top emerging trends in performance testing that one should watch out for in the next few years. However, given the unprecedented changes, we might see the addition of these new trends much sooner in the future. Similarly, some of the emerging trends may vanish before they become mainstream due to various challenges in implementing them on a larger scale. Businesses, testers, and individuals will need to keep themselves updated about new developments in the industry to stay ahead of the curve.

Why choose Yethi for performance testing?

Yethi is a niche QA service provider for global banks and financial institutions that offers efficient end-to-end testing. Our flagship, Tenjin, is a codeless test automation platform that can carry out all aspects of functional and non-function testing with nearly 100% accuracy. Tenjin executes high-level performance testing to identify the responsiveness, availability, and scalability of the system. It performs multiple rounds of tests to check the consistency of the system. Our aim is to ensure that your application performs at its best even during increased, load, stress, and volume.

Code Coverage Vs. Test Coverage

Improving the ‘quality’ of software is the key to creating a loyal customer base and increasing the ROI. There are different metrics to assess the software quality, the most important ones are code coverage and test coverage. Sometimes both are used interchangeably, however, they are not the same. Both are used to measure the effectiveness of the code, hence, giving a clear picture of the quality of the software and deciding if the product is ready for deployment.

As code and test coverage are necessary to evaluate the efficiency of the code used in developing the software; let’s shed light on how code coverage and test coverage differ from each other and help in providing an insight to the software quality.

What is Code Coverage?

Code coverage is performed to analyse the code execution length. It is a software testing practice that determines the extend to which the code has been executed by observing the critical lines in the code across the length. Further, it helps in validating the code for understanding the robustness of the final outcome.

Code coverage is a white-box testing technique that generates a report that details how much of the application code has been executed, making it easy to develop enterprise-grade software products for any software company.

How is Code Coverage Performed?

Code coverage is fundamentally performed at the unit testing level by considering various criteria. Here are a few critical coverage criteria that most companies practice:

Function Coverage: covers the functions in the source code that are called and executed at least once.

Statement Coverage: covers the number of statements that have been successfully implemented in the source code.

Path Coverage: covers the flows containing a series of controls and conditions that have operated well at least once.

Branch Coverage: covers the decision control structures like loops that have been executed without errors.

Condition Coverage: covers the Boolean expressions validated and performs both TRUE and FALSE as per the test runs.

Loop Coverage: covers the completed loop body zero times, exactly once or more than once.

What is Test Coverage?

Unlike code coverage, test coverage is a black-box testing procedure that provides data about the tests performed on an application or website. It controls the number of tests that have been completed by deciding the area of a requirement not executed by a set of test cases.

Test coverage helps to create additional test cases to ensure the maximum range of requirements is outlined in multiple documents like:

  • FRS (Functional Requirements Specification)
  • SRS (Software Requirements Specification)
  • URS (User Requirement Specification)

Additionally, it helps identify a quantitative measure of test coverage, which is an indirect method for quality checks.

How is Test Coverage Performed?

Test coverage can be accomplished by practicing static review procedures like peer reviews, inspections, and walkthroughs by transforming the ad-hoc defects into executable test cases.

It is performed at the code level or unit test level using automated code coverage or unit test coverage tools. In contrast, functional test coverage can be done with the help of proper test management tools.

Here are a few critical coverage criteria that most companies practice:

  • Functional testing: Functional testing evaluates the features against requirements specified in the Functional Requirement Specification (FRS) documents.
  • Acceptance testing: Acceptance testing verifies whether a product is suitable to be delivered for customer use.
  • Unit testing: Unit testing is performed at the unit level, where the bugs are extensively different from problems found at the integration stage.

Significant Differences Between Code Coverage and Test Coverage

Here are some of the prime differences between code and test coverage:

Code Coverage Test Coverage
Refers to which application code is exercised when the application is running Refers to how well the Number of tests
executed covers the functionality of an application
Helps in measuring how efficiently the test execution can be achieved Provides new test cases, which helps to improve the test coverage and, in return, increases the defects
Checks the quantitative measurement Helps identify the measure of test cases, which enhances the quality of the software
Helps in testing the source code Eliminates test cases that are not useful and do not increase the test coverage of the software
Defines the degree of testing Helps find the areas that are not implemented by any test cases
Performed by developers Performed by the QA Team

Method to Calculate Code and Test Coverage

The formulas for calculating various coverages of code are:

Code Coverage

Statement Coverage can be calculated as the number of executed statements/Total number of statements X 100

Function Coverage can be calculated as the number of functions called/Total number of functions X 100

Branch Coverage can be calculated as the number of executed branches/Total number of branches X 100

Example: If the total number of executed branches are 6 and the total number of branches is 7, then the branch coverage will be 6/7*100 = .85

Test Coverage

In the first step, calculate the total number of lines in the software under test.

Then in the second step, calculate the number of lines of all the codes of all the test cases currently under execution.

Then divide the count in step one by count in step two.

The result is then multiplied by 100 to get the percentage of test coverage that is covered. 

Example: If the total number of lines in a code is 500 and the number of lines executed in all is 50, the test coverage is 500/50 * 100 = 10%.


In this fast-paced, technology-driven world, understanding code coverage and test coverage are necessary for developers and testers. These coverages help strengthen and simplify the code so that the resulting application is the highest possible quality. However, developers and QAs can build result-driven, modern code that sets the foundation of genuinely great software by executing these concepts.

Importance of UI and UX Testing and Yethi’s Role

Creative designs and seamless navigation of the website determines the fate of how well the organizations connect with their audience. Only a visually appealing (UI) application with an easy user interface (UX) can stand out in the crowd, attract new customers, and retain the existing ones. Both, a good UI design and an exceptional UX design are necessary to offer a seamless and impactful user experience, failing which the company’s reputation would be severely affected. Hence, it is essential to carry out detailed UI/UX testing to make sure they work without any flaws.

The UI and UX parameters are critical for improved user experience and creating new inclusions of a smarter and future-oriented reality that will take your business to newer heights. Let’s understand what UI/UX is and why testing them is crucial.

What is UI testing?

UI, stands for the user interface, is the design layout of applications running on multiple operating systems. UI testing ensures that the application elements and stages, including the links and buttons, work without disruptions. Through UI testing, the developers and testers continuously enhance the application quality by fixing all its elements and functionalities.

What is UX testing?

UX, is the abbreviation to user experience, ensures end-users response, engagement and association with the website or mobile application. UX testing includes the overall look and feel of the website considering the user engagement. Whenever the company adds some new features to its product, the testers must perform UX testing to check how it impacts the user experience. Frequent feedback from the customers will help improve the product.

Importance of UI and UX testing

Businesses aim to improve their efficiency and profitability, acquire new customers, and retain the older ones. With this being the focus, it is essential to approach business smartly and intelligently. Companies need to learn different user perspectives so that products and services can meet customer expectations.

Through User interface testing (UI testing), testers ensure that the buttons, fields, labels, and other items on the screen work without any functionality errors. UI testing further checks the control over toolbars, colour, fonts, buttons, sizes, icons, and more and how these functionality responds, whenever there is some input from the users. User Interface tells us how the user interacts with the mobile and website applications. Testing of UI removes the blockage so that the users are easily able to connect with the software. The four parameters to check the product

UI of tested products are:

  • Easy to use and easy to navigate
  • Use consistency for the users
  • Easy user access of information and features  
  • Application compatible for uninterrupted performance

Sometimes users purchase and use a product followed by customer reviews, while others would opt for a product based on application interface and user experience. Every customer has a particular purpose for using applications. UX testing helps in identifying and achieving these purposes. When customers use products, they wish to obtain maximum value; hence, it becomes important to deliver applications of higher quality.

Through UX testing, an organisation ensures that they provide a fully functional quality software or application to the customers enabling them to navigate through the app without experiencing system errors or malfunctions. UX testing allows you to find a few of the core issues of applications, which are as follows:

  • Identifying the damaged links
  • Fixing the page errors
  • Resolving the content and language issues
  • Solving poor page design layout
  • Focus on enhancing messaging, images, and branding
  • Ensuring site and application uniformity

The smallest modification in the application interface, at the development stage, may have a significant impact on the software functionalities. Since the development team frequently incorporates changes in the User Interface, the UI and UX testing must be an integral part of the continuous development process. Since it is affordable to fix the UI bugs in the development phase, companies are likely to avoid incurring the cost during the product release by testing the application UI at the development stage.

Benefits of UI and UX tests


It is essential to build a high-quality product development and ensure the application performance rather than fixing the design. Conducting usability testing just before releasing the product to the market can help save more time and money. It also ensures customer satisfaction. It can bring down on unnecessary expenses and help you release an error-free product in the market.

High Conversion Rate

Website usability testing ensures improved user experience, which helps in enhancing website conversion rates by up to 75%. By improving the UI and UX of applications you are aiming to offer your users a fully functional application, which ensures complete user satisfaction. The user experience encourages long-term commitment from your users. By welcoming constructive feedback from your users, you encourage them to provide you with fresh ideas to improve your application functionality, further improving the product quality.

Brand awareness and loyalty

All businesses have different purposes and accordingly, they release solutions. But the success of each solution depends on how well your users relate to the brand. The secret of establishing brand success depends on how your users are encouraged to use the solution. The users must have an adequate understanding of the solutions provided to them so that the organisations are able to build brand affinity and expand the strength of their target audience.

Yethi’s Role as UI / UX Testing Partner

Banking is leaping towards digitalisation, and as a result, companies are investing in applications to gain more mobility. There are diverse mobile applications, and each comes with several challenges. To overcome these challenges testing across multiple devices and networks is essential.

At Yethi, we offer exhaustive test coverage throughout all aspects of digital transformation. From UX and UI testing to functional, compatibility, usability as well as security, we provide test across a large set of devices, OS, and browsers.

Yethi’s test automation solution, Tenjin, ensures quality testing of data elements on your digital and mobile assets. It incorporates real-time testing of native and hybrid mobile applications across diverse platforms, thereby eliminating delays and redundancies. Tenjin can reduce the testing time by 15-20% as it has a domain-specific test library of over half a million test cases.


When it rolls down to UX and UI testing, Yethi’s test management solution delves into the essential aspects of testing. To significantly bring down the testing time of an application, we follow the test selection method, i.e., we pick and choose only those test cases relevant to your domain. Having a collective industry experience of more than 25 years, we understand the importance of end-to-end development flow to minimize UI and UX issues and errors.

[INFOGRAPHIC] Manual Vs Automated Testing

Software testing has evolved from tedious manual testing processes to automated solutions. As software development processes are getting complex and moving towards a more agile approach, manual testing can be time-consuming while lacking accuracy and consistency due to its mundane nature. To ensure the quality of the software is the best, organizations are adapting test automation solutions that will also significantly reduce time, cost, and effort.

Take a look at the below infographic to understand the difference between Manual and Automated Testing, and decide which one to choose.


Manual Vs Automated Testing

Though, automation testing is preferred by most of the organizations today, manual testing cannot be eliminated from the process completely. Manual testing is required to set the initial automation process. However, automated testing is best suited for regression testing, repeated test execution, and performance testing.

Risks Associated with Data Migration and How to Mitigate Them

Let’s begin with some numbers! According to IndustryARC, the global data migration market that emphasizes Cloud-based servers over on-premises ones is predicted to reach an estimation of $10.98B by early 2022. In addition to this stat,  the Cisco Global Cloud Index shows that  Cloud traffic is expected to reach 7680 Exabytes in North America alone! Similar enhancements in modern data management technology bring more efficiency and transparency, which will directly surge the adaptation of application and data migration in small-scale and large-scale enterprises.

Given the risks associated, the question “Is data migration really important?” isn’t unusual. And the answer must always be “Yes!” Delaying data migration while holding onto outdated IT infrastructure isn’t an option with increasing market intrusion from non-traditional competitors who can create more nimble and responsive approaches towards delivering unique products. Because monolithic application systems weren’t designed to quickly adapt to business dynamics, they have to be replaced. Failing which, may pose further risks of losing market share and retention.

Let’s understand data migration first

At its core, data migration is the process of transferring data from one location to another, from one application to another, or from one format to another. This crucial step towards improvising an outdated IT infrastructure is generally taken during the installation of new systems or upgrading legacy ones, which will share the same dataset without affecting live operations. In recent years, the majority of data migrations are executed for transferring actionable data from on-premises infrastructure to Cloud-based options, that too, while undertaking data migration testing.

Concerns with legacy systems

The primary focus of IT infrastructure has already shifted towards better performing, more efficient, cost-effective, and secure solutions. CEOs and IT admins are struggling to maintain or support legacy systems as common challenges in legacy designs are time-consuming to tackle while the technology is mostly unfamiliar to new-age IT personnel. Some of the key concerns of using legacy systems include:

  • Heavy Maintenance Costs: Legacy systems are now obsolete, primarily, because of higher maintenance and operational costs. Further, the poor performance of such legacy systems cannot support new business initiatives.
  • System Failures: With legacy IT infrastructure, system failures are a daily occurrence. Since the professionals who implemented such systems have retired, new-age IT admins lack the skills to maintain legacy systems.
  • The Inability of Processing Complex Data: Within legacy systems lies old technology and computer systems that are fundamentally unable to execute complex enterprise operations with enough speed or reliability.

The increasing challenges to using legacy systems in today’s tech-driven world has led to migrating to new-age systems to keep up with the trend. However, migration to new systems may come with a set of potential risks which the organization should be able to mitigate and yield the best outcome from the migration.

Potential risks of data migration

  • Lack of Transparency: Not allowing key stakeholders to input in the undergoing data migration process is the mistake often made by enterprises. At any stage, someone might need the system to remain operational or would care if the data is being migrated, therefore, it’s vital to maintain complete transparency on the process.
  • Lack of Expertise or Planning: The primary cause leading to unsuccessful data migration is lack of expertise. With modern systems getting complex with millions of data points, it’s essential to evaluate which data points must stay operational. As data migration is more about risk mitigation, any disruption may leave IT admins clueless.
  • Addressing Data Privacy with Proven Migration Plans: When an enterprise doesn’t assess how many people might receive access to the data in the migration process, potential data breaches can occur. Conducting any data migration always requires proven migration strategies that further raise the probability of its success.
  • Defective Target Systems: Projects and vendors must be managed parallelly while flipping the switch from legacy systems to new-gen infrastructure. Suppose an error occurs in either the source system or the target system, it may derail the migration process in the middle of transferring vital data, raising the risk for data corruption.
  • Trying to Execute Complex Data Conversion: Unnecessarily making the migration process complex without any tangible increase in outcomes must be avoided at all costs. Complex conversions add extra steps to the process that just makes it challenging to execute. Only undertaking essential migration steps will surely get it done fast.

Why is data migration more about risk mitigation?

As legacy systems are growing organically, the need to adapt to modern business applications are raising concerns with their data quality. There might be millions of data points that must be assessed before concluding which ones must stay operational for any enterprise-scale migration. Along with regulatory and analytical needs, the data must be Extracted, Transformed, and Loaded (ETL) to modern systems without disrupting major business applications. As datasets get complex, things are no longer so simple!

The importance of conducting data migration testing

Once the data has been Extracted, Transformed, and Loaded (ETL) into new-gen systems, what stops it from being deployed? The answer is Data Migration Testing! As enterprises are swiftly migrating their operations to the Cloud, ensuring the integrity of data is key to ensuring further business applications. Here’s how enterprises achieve it:

Data-level validation testing

With certain data migration testing tools, data-level validation testing ensures that the dataset has been efficiently migrated to the target system without any disruptions. With data-level validation testing, data will be verified at:

  • Level 1 (Row Counts): Verifies the number of records migrated from the legacy system to the target.
  • Level 2 (Data Verification): Verifies data accuracy from any selected portion of the total migrated database.
  • Level 3 (Entitlement Verification): Verifies the destination database setup for users and selected data samples.

Application-level validation testing

In contrast, the functionality of the sample application is validated with application-level validation testing. This ensures the smooth operation of the application with the new infrastructure using specific data migration testing tools.


If you are concerned about the risks associated with data migration, you’d be relieved to know that the benefits far outweigh the risks. The importance of expertise and planning is still evident in data migration and data security concerns. In addition to having an efficient and rock-solid data migration strategy, enterprises must also practice data migration testing. Data migration processes remain an activity with potential risks, successfully testing can drastically reduce the migration errors while optimizing future data migration processes.